@conference {
	title = {Stability, Parameter Estimation and Adaptive Control for Discrete-Time Competing Queues},
	author = {Baras, John S., Dorsey, Arthur J., Makowski, Armand M.},
	year = {1984},
	month = {12/1984},
	abstract = {In this paper, several discrete-time queues compete~at the beginning of each time slot for the attention of a single server with infinite capacity. The service requirements are geometric with queue-dependent parameters, independent from customer to customer and independent from the arrivals. The stability of such systems is characterized under the action of an arbitrary , not necessarily Markovian, service allocation policy. Maximum likelihood estimates are obtained in explicit form for the service rates and their strong consistency is established.The results are then applied to the problem of adaptively controlling such systems when the service rates are unknown, under the long-run average performance criterion with instantaneous cost linear in the queue sizes.},
	address = {Las Vegas, Nevada},
	booktitle = {The 23rd IEEE Conference on Decision and Control},
	pages = {pp. 1149-1157}
}
@conference {
	title = {Discrete-Time Competing Queues with Geometric Service Requirements:  Stability, Parameter Estimation and Adaptive Control},
	author = {Baras, John S., Dorsey, Arthur J., Makowski, Armand M.},
	year = {1984},
	month = {05/1984},
	abstract = {In this paper, several discrete-time queues compete at the beginning of each time slot for the attention of a single server with infinite capacity. The service requirements are geometric with queue dependent parameters, independent from customer to customer and independent from the arrivals. The stability of such systems is characterized under the action~of an arbitrary, not necessarily Markovian, service allocation policy. Maximum likelihood estimates are obtained in explicit form for the service rates and their~strong consistency is established. The results are then applied to the problem of adaptively controlling such systems when the service rates are unknown, under the long-run average performance criterion with instantaneous cost linear in the queue sizes.},
	address = {San Francisco, California},
	booktitle = {1984 Joint TIMS/ORSA Meeting}
}
@conference {
	title = {Two Competing Queues with Linear Costs: The  μc-rule is Often Optimal},
	author = {Baras, John S., Dorsey, Arthur J., Makowski, Armand M.},
	year = {1983},
	month = {12/1983},
	abstract = {A discrete-time model is presented for a system of two queues competing for the service attention of a single server with infinite buffer capacity. The service requirements are geometrically distributed and independent from customer to customer as well as from the arrivals. The allocation of service attention is governed by feedback policies which are based on past decisions and buffer content histories. The cost of operation per unit time is a linear function of the queue sizes. Under the model assumptions, a fixed prioritization scheme, known as the uc-rule, is shown to be optimal for the expected long-run average criterion and for the expected discounted criterion, over both finite and infinite horizons. Two different approaches are proposed for solving these problems. One is based on the dynamic programming methodology for Markov decision processes, and assumes the arrivals to be i.i.d. The other is valid under no additional assumption on the arrival stream and uses direct comparison arguments. In both cases, the sample path properties of the adopted state-space model are exploited.},
	address = {San Antonio, Texas},
	booktitle = {22nd IEEE Conference on Decision and Control},
	pages = {pp. 186-209}
}
@conference {
	title = {Two Competing Queues with Linear Costs and Geometric Service Requirements},
	author = {Baras, John S., Dorsey, Arthur J., Makowski, Armand M.},
	year = {1983},
	month = {12/1983},
	abstract = {A discrete-time model is presented for a system of two queues cmompeting for the service attention of a single server with infinite buffer capacity. The service requirements are geometrically distributed and independent from customer to customer as well as from the arrivals. The allocation of service attention is governed by feedback policies which are based on past decisions and buffer content histories. The cost of operation per unit time is a linear function of queue sizes. Under the model assumptions, a fixed prioritization scheme known as the~{\textmu}c-rule, is shown to be optimal for the long run average criterion and for the expected discounted-criterion, over both finite and infinite horizons. Two different approaches are proposed to solve these problems. One is based on dynamic programming methodology for markov decision processes, and assumes the arrival to be i.i.d. The other is valid under no additional assumptions on the arrival streams and uses direct comparision arguments. In both cases the sample path properties of the adopted state-space model are exploited.},
	address = {San Antonio, Texas},
	booktitle = {22nd IEEE Conference on Decision and Control},
	pages = {pp. 1173-1178}
}
@conference {
	title = {Adaptive Control of Two Competing Queues},
	author = {Baras, John S., Dorsey, Arthur J.},
	year = {1983},
	month = {04/1983},
	abstract = {The adaptive control of two queues competing for the services of a single server is treated. The arrival rates and service rates are considered constant but unknown. Convergence results for certainty-equivalence type, adaptive control schemes are established. Several possible extensions of the results are discussed briefly.},
	address = {San Diego, California},
	booktitle = {1983  IEEE International Conference on Computer Communications (INFOCOM)},
	pages = {pp. 427-435}
}
@conference {
	title = {Adaptive Control of Two Competing Queues},
	author = {Baras, John S., Dorsey, Arthur J.},
	year = {1983},
	month = {04/1983},
	abstract = {We consider the problem of optimally all locating the time of a server to two parallel queues. "First we consider the problem when the queue sizes are observed, although the arrival and departure rates are not available, but have to be estimated. We next consider the problem when the arrival process is observed, but its rate is unknown, while the departure process is not observed and its rate known within certain bounds. In both cases adaptive control schemes are developed. The performance criterion used is aggregate delay .},
	address = {Chicago, Illinois},
	booktitle = {The 1983 Institute for Operations Research and the Management Sciences Joint ORSA/TIMS Meeting (INFORMS)},
	pages = {pp. 104}
}
@conference {
	title = {On the Point Process Disorder Problem and Applications to Urban Traffic Estimation},
	author = {Dorsey, Arthur J., Baras, John S., Levine, William S.},
	year = {1979},
	month = {03/1979},
	abstract = {We consider here the point process disorder problem in its generality and we develop the maximum likelihood and MAP estimates of the disorder time T. Applications of the results to the platoon determination problem in urban traffic show that both estimators outperform previous solutions to the problem.},
	address = {Baltimore, MD},
	booktitle = {1979 Conference on Information Sciences and Systems},
	pages = { pp. 37-42},
	organization = {Johns Hopkins University}
}
@conference {
	title = {Traffic Estimation Based On Point Process Models},
	author = {Baras, John S., Levine, William S., Dorsey, Arthur J., Lin, Tahsin L.},
	year = {1979},
	month = {02/1979},
	abstract = {Two families of models for the relation between detector data and the flow of traffic on urban streets are developed. The first describes the relation between the queues at traffic signal and data from nearby detectors. The second model~headways statistics for urban traffic thereby relating detector data to the passage of platoons of vehicles. Recent results in the theory of point processes then give the non-linear minimum error variance filters/predictors corresponding to these models. It is shown that these optimal~estimators are computationally feasible in a microprocessor. The algorithm also performs very well when tested using data derived from UTCS-I traffic simulation.},
	address = {Asilomar conference grounds, Pacific Grove,  CA},
	booktitle = {Engineering Foundation Conference on Issues in Control of Urban Traffic Systems},
	pages = {pp. 266-285}
}
@conference {
	title = {Estimation of Traffic Platoon Structure from Headway Statistics},
	author = {Baras, John S., Levine, William S., Dorsey, Arthur J.},
	year = {1978},
	month = {12/1978},
	abstract = {This paper deals first with the modeling of urban traffic headway statistics. It is shown that a composite distribution based on the convex combination of a lognormal and a shifted exponential distribution gives a good fit to observed traffic data. This statistical model is then used to generate a model for the formation and passage of "platoons" of vehicles. It is shown that the problem of estimating the time at which a "platoon" passes a detector, as well as the number of vehicles in the disorder "platoon", problem. corresponds An optimal to the estimator point process for the platoon size and passage time, based on detector data, is then derived via known results for the point process disorder problem. It is shown that the computations required by~this estimator can be performed~in a microprocessor. required by this Furthermore, the estimator is tested against the UTCS-1 traffic simulator and performs very well. Parameter sensitivity analysis of the estimator is presented. Finally, the use of these results to improve the filter/predictor described in a companion paper, and vice versa, is explained.},
	address = {San Diego, CA},
	booktitle = {17th IEEE Conference on Decision and Control},
	pages = {pp. 697-703}
}
@article {
	title = {Two Competing Queues with Linear Costs and Geometric Service Requirements},
	author = {Baras, John S., Dorsey, Arthur J., Makowski, Armand M.},
	year = {1985},
	month = {01/1985},
	abstract = {A discrete-time model is presented for a system of two queues competing for the service attention of a single server with infinite buffer capacity. The service requirements are geometrically distributed and independent from customer to customer as well as from the arrivals. The allocation of service attention is governed by feedback policies which are based on past decisions and buffer content histories. The cost of operation per unit time is a linear function of queue sizes. Under the model assumptions, a fixed prioritization scheme known as the~{\textmu}c-rule, is shown to be optimal for the long run average criterion and for the expected discounted-criterion, over both finite and infinite horizons. Two different approaches are proposed to solve these problems. One is based on dynamic programming methodology for Markov decision processes and assumes the arrival to be i.i.d. The other is valid under no additional assumptions on the arrival streams and uses direct comparison arguments. In both cases, the sample path properties of the adopted state-space model are exploited.},
	pages = {pp. 186-209},
	volume = {Vol. 17},
	journal = {Advances in Applied Probability}
}
@article {
	title = {Stochastic Control of Two Partially Observed Competing Queues},
	author = {Baras, John S., Dorsey, Arthur J.},
	year = {1981},
	month = {10/1981},
	abstract = {We consider the dynamic control of two queues competing for the services of one server. The problem is to design a server time allocation strategy, when the sizes of the queues are not observable. The performance criterion used is total expected aggregate delay. The server is assumed to observe arrivals but not departures.

This problem is formulated as a stochastic optimal control problem with partial observations. The framework we adopt is that of stochastic control in discrete time and countable "state space." The observations are modeled as discrete time, 0-1 point process with rates that are influenced by a Markov chain. Examples from computer control of urban traffic are given, to illustrate the practical motivation behind the present work, and to relate to earlier work by us on the subject. A particular feature of the formulation is that the observations are influenced by transitions of the state of the Markov chain. The classical tools of simple Bayes rule and dynamic programming suffice for the analysis. In particular, we show that the "one step" predicted density for the state of the Markov chain, given the point process observations is a sufficient statistic for control.

This framework is then applied to the specific problem of two queues competing for the services of one server. We obtain explicit solutions for the finite time expected aggregate delay problem. The implications of these results for practical applications as well as implementation aspects of the resulting optimal control laws are discussed.},
	pages = {pp. 1105-1117},
	volume = {AC-26},
	journal = {IEEE Transactions on Automatic Control.}
}
@article {
	title = {Estimation of Traffic Platoon Structure from Headway Statistics},
	author = {Baras, John S., Dorsey, Arthur J., Levine, William S.},
	year = {1979},
	month = {08/1979},
	abstract = {This paper deals first with the modeling of urban traffic headway statistics. It is shown that a composite distribution based on the convex combination of a lognormal and a shifted exponential distribution gives a good fit to observed traffic data. This statistical model is then used to generate a model for the formation and passage of "platoons" of vehicles. It is shown that the problem of estimating the time at which a "platoon" passes a detector, as well as the number of vehicles in the "platoon" corresponds to the point process disorder problem. An optimal estimator for the platoon size and passage time, based on detector data, is then derived via known results for the point process disorder problem. It is shown that the computations required for this estimator can be performed in a microprocessor . Furthermore, the estimator is tested against the UTCS-1 traffic simulator and performs very well. Parameter sensitivity analysis of the estimator is presented. Finally, the use of these results to improve the filter/predictor described in a companion paper, and vice versa, is explained.},
	pages = {pp. 553-559},
	volume = {AC-24},
	number = {No. 4},
	journal = {IEEE Transactions on Automatic Control.}
}
